High-efficiency prediction method for helicopter global/ground noise based on near-field acoustic holography

Abstract

Noise reduction program design is an effective approach that relies on efficient noise prediction for reducing ground noise during flight. The existing noise prediction methods have the limitations of being computationally expensive or only applicable to far-fields. In this paper, a High-Efficiency Prediction Method (HEPM) for helicopter global/ground noise based on near-field acoustic holography is proposed. The HEPM can predict the global noise based on acoustic modal analysis and has the advantages of high prediction accuracy and low time cost. The process is given as follows: firstly, the rotor noise on the holographic surface in the specified flight is obtained by simulations or experiments. Secondly, the global noise model, which maps time-domain noise to acoustic modes, is established based on near-field acoustic holography and Fourier acoustic analysis methods. Finally, combined with acoustic modal amplitude, the model established enables efficiently predicting the global/ground noise in the corresponding flight state. To verify the accuracy of the prediction method, a simulation study is conducted in hovering and forward flight states using a model helicopter with a 2-meter rotor and Rotor Body Interaction (ROBIN) fuselage. The comparison of HEPM with numerical results shows that the average prediction errors of the global and ground noise are less than 0.3 dB and 0.2 dB, respectively. For a region containing 100,000 observers, the computation time of the HEPM is only one-fifth of that of the acoustic hemisphere method, demonstrating the rapidity of the proposed method.